CapordiaDescribe what needs to work together
The GPU card is the starting point for the choice, but the application also depends on its environment. A workload may prepare its inputs on the CPU, load its data into system memory and then send operations to the GPU. List these steps in your file so that not every slowdown is attributed to the card itself.
The catalog details the GPU model and memory. For specific CPU, RAM, storage, or connectivity needs, state a measured requirement in your scoping document. This allows you to discuss the necessary scope without inferring specifications that are not part of the configuration.
Distribute tasks before adding more cards
For a queue of independent jobs, define the inputs and outputs of each task. For a single distributed process, identify the mechanism used by your software. The number of cards, the memory per card, and inter-GPU communication answer different questions; the comparison must preserve all three dimensions.
Keep control of your environment
Your team chooses the software and the workloads to run. Capordia does not inspect the content of files, prompts, or computations. Organize access rights, updates, and result copies around the people who actually operate the workload. This division makes intervention simpler when a setting needs to be changed or a task needs to be restarted.
To prepare for what comes next
Explain expectations before looking for a more powerful GPU.
Reconcile expectations, inputs and GPU readings before changing cards.
Choose what advances together before counting cards.
Choose between independent tasks and distributed processing before multiplying GPUs.